Adaptive flow controller for use with a flow control system

ABSTRACT

An adaptive airflow control system for positioning damper systems or controlling air units utilized in an environment control system is provided. The system is based on a fixed-gain, proportional-only feedback design to provide stable operation given the nonlinear behavior of flow through a valve or damper. A time-dependent deadzone of nonlinearity is used to reject measurement noise. The deadzone of nonlinearity is adjusted by an adaptively calculated proportionality constant which is capable of switching the control system between various operating modes for adjusting the performance of the system.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a Continuation-In-Part of U.S. Ser. No.08/448,681, filed May 24, 1995, now U.S. Pat. No. 5,768,121 Jun. 6,1998.

NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by any one of the patentdisclosure, as it appears in the Patent and Trademark Office patentfiles or records, but otherwise reserves all copyright rightswhatsoever.

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention is related to an airflow control apparatus for anenvironmental control system. More particularly, the present inventionis related to an adaptive control system for positioning damper systemsor controlling air units utilized in an environment control system.

2. Discussion

Environment control networks, facility management systems, and dampersystems are employed in office buildings, manufacturing facilities, andappliances for controlling the internal environment of the facility. Forexample, in a heating, ventilating, and air conditioning (HVAC) system,controlled air units (e.g., variable air volume (VAV) boxes, unitarydevices (UNT) or damper systems) are located throughout the facility andprovide environmentally controlled air to the internal environment ofthe facility. The controlled air is provided at a particular temperatureor humidity so that a comfortable internal environment is established.The air flow rate of the controlled air is preferably measured in cubicfeet per minute (CFM).

The VAV boxes are coupled to an air source which supplies the controlledair to the VAV box via duct work. VAV boxes and unitary devices providethe controlled air through a damper. The damper regulates the amount ofthe controlled air provided to the internal environment. The damper iscoupled to an actuator which preferably positions the damper so thatappropriate air flow (in CFM) is provided to the internal environment.

A controller is generally associated with at least one actuator anddamper. The controller receives information related to the air flow andtemperature in the internal environment and appropriately positions theactuator so that the appropriate air flow is provided to the internalenvironment. The controller may include sophisticated feedbackmechanisms such as proportional integral (PI) control algorithms.Sophisticated feedback mechanisms allow the actuator to be positionedmore precisely.

More particularly, the controller generally includes a flow controlsystem for positioning the actuator so that the damper provides adesired amount of air flow. The flow control system typically measuresthe actual air flow across the damper and adjusts the position of theactuator until the desired amount of air flow is provided by thecontrolled air unit. In such systems, the performance of the flowcontrol system (e.g., the accuracy or precision of the position of thesystem damper) is critical to reliability, energy efficiency, andoverall performance of the HVAC system and controlled air unit. Poorflow control often leads to degraded temperature control performance,decreased efficiency for the controlled air unit, and prematuremechanical failures for the actuator and damper system associated withthe unit.

Heretofore, flow controllers or flow control systems in HVAC systems areprone to slow response and poor disturbance rejection due to theinherent non-linear behavior and measurement noise associated withcontrolled air units such as VAV boxes. The measurement of actual airflow is strongly affected by turbulence. Additionally, friction,hysteresis, and non-linear relationships between the flow rate anddamper position complicate the control of damper systems. A traditionalapproach to solving these problems involves the use of proportional,(P), proportional-integral (PI), or proportional-integral-derivative(PID) positioning algorithms for the damper.

Thus, there is a need for a flow controller which is less prone tosluggishness and oscillatory behavior. There is also a need for a flowcontroller which can be set to have a low duty cycle and yet provideacceptable setpoint tracking. Finally, it is desirable to provide a flowcontroller that can quickly switch back and forth between two or moreoperating modes which adaptively control the setpoint trackingperformance.

SUMMARY OF THE INVENTION

The present invention relates to an environment control system whichincludes an air unit which provides air flow to an environment. The airunit is operatively associated with a controller and controls an amountof the air flow in accordance with a flow setpoint signal. Thecontroller includes a flow sensor and a processor. The flow sensor isexposed to the air flow provided by the unit and generates a flow signalrepresentative of an amount of the air flow provided to the environment.The processor is coupled to the flow sensor and configured to cyclicallyreceive the flow signal and generate a controller output signal inresponse to the flow signal and the flow setpoint signal. In oneembodiment, the controller output is provided to the air unit to movethe damper to a position corresponding to the flow setpoint signal. Theprocessor calculates the controller output signal in accordance with asetpoint error signal and a deadzone of nonlinearity. The deadzone ofnonlinearity is calculated in accordance with a standard deviation ofthe flow signal.

The present invention also relates to a controller for use in anenvironment control system which includes an air duct having a damperwhich is operatively associated with an actuator. The actuator positionsthe damper so that the damper provides a rate of air flow to anenvironment in response to an actuator control signal. The actuatorcontrol signal represents the air flow rate and is operatively coupledto the controller. The controller includes sensor means and processormeans. The sensor means generates an actual flow signal. The processormeans is coupled to the sensor means, and cyclically receives the actualflow signal from the sensor means and cyclically generates the actuatorcontrol signal in response to the actual flow signal. The actuator isrelated to a desired rate for the rate of the air flow provided acrossthe damper. The processor means calculates the actuator control signalin accordance with a setpoint error signal and a deadzone ofnonlinearity. The deadzone of nonlinearity is calculated in accordancewith a standard deviation of the actual flow signal.

The present invention also relates to a control system which includes aunit such as a damper or valve for providing flow, a controller forproviding a controller output signal, and a flow sensor for providing anactual flow signal. The unit is operatively associated with a controllerand controls an amount of the flow in accordance with the controlleroutput signal. The flow sensor is exposed to the flow provided by theunit and generates the actual flow signal representative of the amountof air flow. A method of controlling the amount of the flow provided bythe unit comprises the steps of receiving the actual flow signal fromthe flow sensor, determining a setpoint error signal based on a flowsetpoint signal and the actual flow signal, determining the desiredoperating mode, calculating a proportionality constant, calculating adeadzone of nonlinearity in accordance with a standard deviation of theactual flow signal, applying the deadzone of nonlinearity to thesetpoint error signal to develop the controller output signal, andproviding the controller output signal to the unit.

In an alternate embodiment, the processor switches the controllerbetween a first operating mode and a second operating mode in responseto a set of conditions associated with the flow setpoint signal. Thefirst operating mode is a default mode. The processor changes theproportionality constant stepwise from a first predetermined constant toa second predetermined constant thereby instantaneously switching theenvironment control system from the first operating mode to the secondoperating mode in response to a predetermined change in the setpointsignal for closely tracking changes in the setpoint error signal.Additionally, the processor can exponentially changes theproportionality constant from the second predetermined constant to thefirst predetermined constant thereby gradually switching the environmentcontrol system from the second operating mode to the first operatingmode in response to a predetermined change in the flow signal fornormally tracking changes in the setpoint error signal. The deadzone ofnonlinearity operates to dampen small adjustments to the actuatorcontrol signal, thereby reducing the actuator duty cycle.

The flow controller of the present invention advantageously requires fewcomputations and does not require tuning. In another aspect of theinvention, the flow controller is coupled to a memory which receives thedeadzone of nonlinearity and recalculates the deadzone of nonlinearitydata after each cycle. The flow controller is preferably implemented ina software program.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will hereafter be described with reference to theaccompanying drawings, wherein like numerals denote like elements, and:

FIG. 1 is a simplified schematic block diagram of an environment controlsystem;

FIG. 2 is a more detailed schematic block diagram of a controller and aVAV box for use in the environment control system illustrated in FIG. 1;

FIG. 3 is a more detailed schematic block diagram of the controllerillustrated in FIG. 2;

FIG. 4 is a block diagram of the software-based control algorithm forthe controller shown in FIG. 3;

FIG. 5 is a diagram illustrating the calculation of the pulse widthsignal based on the pulse width modulation function for the controllershown in FIG. 3;

FIG. 6 is a diagram illustrating the calculation of the controller errorsignal based on the setpoint error signal and the deadzone ofnonlinearity for the controller shown in FIG. 3;

FIGS. 7A-7B show pseudo code in accordance with an exemplary aspect ofthe present invention;

FIG. 8 is a block diagram of the software-based control algorithmassociated with an alternative preferred embodiment of the presentinvention which is also compatible with the controller shown in FIG. 3;

FIGS. 9A-9B show the pseudo code of an exemplary software algorithmwhich implements the control algorithm of FIG. 8 in accordance with thealternate preferred embodiment of the present invention; and

FIG. 10 shows the graph of an exemplary proportionality constant versusdiscrete time.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Referring to FIG. 1, the present invention may be utilized in anenvironment control network or system 10. Although the present inventionis described below for use in an HVAC environment, the flow controllerof the present invention may be utilized in any fluid flow application.For example, the flow controller of the present invention may be used inliquid supply systems such as those used in petroleum or chemicalprocessing industries or other flow applications such as those in foodpreparation, material treatment plants or any industry utilizingcontrolled flow of material.

Environment control system 10 includes a work station 12, a station 14,a station 16, a controller 20, a controller 24, and a controller ormodule 30. Controllers 20, 24 and module 30 are coupled with station 14via a communication bus 32. Work station 12, station 14 and station 16are coupled together via a communication bus 18. Station 16 is alsocoupled to a communication bus 17. Communication bus 17 may be coupledto additional sections or additional controllers, as well as othercomponents utilized in environment control system 10.

Preferably, environment control system 10 is a facilities managementsystem such as the Metasys™ system as manufactured by Johnson Controls,Inc. (JCI) for use with VAV boxes 38 and 40. Alternatively, system 10can be a unitary system having roof-top units or other damper systems.Stations 14 and 16 are preferably an NCU station manufactured by JCI,and controllers 20 and 24 are VAV 100-0™ controllers manufactured by JCIor other controllers known in the art. Controller or module 30 ispreferably an air handler control unit (AHU) such as a AHU 102-0™ unitmanufactured by JCI for monitoring and effecting the operation of an airhandler (not shown) which provides forced air for system 10.

Communication buses 17 and 32 are N2 buses preferably comprised of atwisted pair of conductors, and communication bus 18 is a LAN (NI) busfor high level communications. Bus 18 is a high speed bus using ARCNET™or Ethernet protocol. Work station 12 and stations 14 and 16 includeEthernet or ARCNET communication hardware. Buses 17 and 32 utilize theRS485 protocol. Controllers 20 and 24, module 30, and stations 14 and 16include RS485 communication hardware. Preferably, controllers 20 and 24,stations 14 and 16, and work station 12 include communication softwarefor transmitting and receiving data and messages on buses 17, 18 and 32.

Controller 20 is operatively associated with a controlled air unit suchas VAV box 38, and controller 24 is operatively associated with acontrolled air unit such as VAV box 40. Controller 20 communicates withwork station 12 via communication bus 32 through station 14 andcommunication bus 18. Preferably, station 14 multiplexes data overcommunication bus 32 to communication bus 18. Station 14 operates toreceive data on communication bus 32, provide data to communication bus18, receive data on communication bus 18, and provide data tocommunication bus 32. Station 14 preferably is capable of otherfunctions useful in environment control system 10. Work station 12 ispreferably, but not limited to, a PC/AT computer or may be a portablecomputer which is coupled to communication bus 18.

The following is a more detailed description of controller 20 and VAVbox 38 with reference to FIG. 2. Controller 20 is preferably a directdigital control (DDC) which includes a communication port 34 coupledwith communication bus 32 (FIG. 1). Controller 20 preferably includes anair flow input 56, a temperature input 54, and an actuator output 74.VAV box 38 may also advantageously include heating or cooling units fortreating an air flow 64. Inputs 54 and 56 are preferably analog inputsreceived by an AID converter (not shown) in controller 20. Controller 20preferably includes circuitry and software for conditioning andinterpreting the signals on inputs 54 and 56.

VAV control box 38 preferably includes a damper 68, an air flow sensor52, and an actuator 72. Actuator 72 positions damper 68 and ispreferably an electric motor based actuator. Many controllers usesynchronous AC motors with dual winding as actuator 72. Alternatively,actuator 72 and controller 20 may be a stepper motor, solenoid,pneumatic device or any other type of device for controlling andpositioning damper 68. Actuator 72 is preferably an EDA-2040™ motormanufactured by JCI having a full stroke time (T_(stroke)) of 1, 2, or5.5 minutes for a 90° stroke.

The position of damper 68 controls the amount of air flow 64 provided toenvironment 66. Environment 66 is preferably a room, hallway, building,or portion thereof or other internal environment. Air flow sensor 52preferably provides an air flow parameter across conductor 58 to airflow input 56. The airflow parameter represents the amount of air flow64 provided through damper 68 to an environment 66.

Controller 20 provides an actuator output signal to actuator 72 fromactuator output 74 via a conductor 76. Controller 20 receives atemperature signal from a temperature sensor 50 across a conductor 60 attemperature input 54. Temperature sensor 50 is generally a resistivesensor located in environment 66.

Air flow sensor 52 is preferably a differential pressure (ΔP) sensorwhich provides a ΔP factor related to airflow (volume/unit time,hereinafter CFM airflow). CFM airflow may be calculated by the followingequation: ##EQU1## where: ΔP is the differential pressure from air flowsensor 52;

Box Area is the inlet supply cross-section area in square feet; and

K is a CFM multiplier representing the pickup gain of the air flow.

The value K and value of box area are stored in a memory (not shown) incontroller 20 when controller 20 is initialized or coupled with VAV box38. The value of box area is generally in the range of 0.08 to 3.142feet squared, and the value of K is generally between 0.58 and 13.08.The value of box area and K may be advantageously communicated fromcontroller 20 to work station 12 so that service people do not have tootherwise obtain these values from paper data sheets and files. Air flowsensor 56 is preferably a diaphragm-based pressure sensor.

With reference to FIGS. 1 and 2, the operation of environment controlsystem 10 is described as follows. Controllers 20 and 24 are configuredto appropriately position actuator 72 in accordance with a cyclicallyexecuted control algorithm. In accordance with the algorithm, controller20 receives the air flow signal at input 56, the temperature signal atinput 54, and other data (if any) from bus 32 at port 34 every cycle,preferably every 1.5 seconds or, alternatively, 1.0 seconds, dependingon the controller algorithm. Controller 20 provides the actuator outputsignal at the actuator output 74 every cycle to accurately positiondamper 68 so that environment 66 is appropriately controlled (heated,cooled, or otherwise conditioned). Thus, controller 20 cyclicallyresponds to the air flow signal and the temperature signal andcyclically provides the actuator output signal to appropriately controlinternal environment 66.

Preferably, the actuator output signals are pulse width signals whichcause actuator 72 to move forward, backward, or stay in the sameposition, and controller 20 internally keeps track of the position ofactuator 72 as it is moved. Alternatively, actuator 72 may providefeedback indicative of its position, or the actuator signal may indicatethe particular position to which actuator 72 should be moved.

FIG. 3 is a more detailed block diagram of controller 20 in accordancewith an exemplary aspect of the present invention. Controller 20includes a processor 100 coupled with actuator output 74, temperatureinput 54, air flow input 56, and communication port 34. Processor 100 ispreferably an 8OC652 processor and communication port 34 is coupled witha twisted pair of conductors comprising communication bus 32 (FIG. 1).

Controller 20 also includes a memory 102. Memory 102 may be any storagedevice including but not limited to a disc drive (hard or floppy), aRAM, EPROM, EEPROM, flash memory, static RAM, or any other device forstoring information. Preferably, memory 102 includes RAM and an EEPROMfor storing air flow control algorithm data. Memory 102 is coupled tothe processor via an internal bus 106.

In operation, processor 100 cyclically samples signals at temperatureinput 56, actuator output 74, and air flow input 56 and performsmathematical operations on these signals. The mathematical operationsgenerate parameter values representative of the signals at inputs 54 and56 and output 74.

With reference to FIG. 4, the operation of system 10 in a dynamicenvironment 137 is represented in a flow control diagram. Controller 20is programmed to operate as a flow controller circuit 125 whichgenerates an actuator output signal u(t) to position damper 68 (FIG. 2).Circuit 125 includes an anti-aliasing filter 128, a sampler 130, acontroller error circuit 132, a controller output circuit 134 and atimer 136.

Air flow sensor 52 (FIG. 2) generates a continuous time measurementsignal z(t). A flow signal f(t) is representative of the amount of airflow to environment 137, and is typically corrupted by noise which isrepresented by n(t). The combination of the measurement noise signaln(t) and the flow signal f(t) is represented by the continuous timemeasurement signal z(t) provided by sensor 52.

An analog low-pass anti-aliasing filter 128 receives and filters thecontinuous time measurement signal z(t) so noise at frequencies higherthan the Nyquist frequency of sampler 130 is rejected. Sampler 130receives the filtered continuous time measurement signal z(t) andprovides the filtered signal z(t) to controller error circuit 132 as adiscrete air flow signal z(k) which represents the measured air flowsignal from flow sensor 52 at the kth instant in time. Controller errorcircuit 132 receives the discrete air flow signal z(k) from sampler 130and computes a controller error signal e_(c) (k) based on apreviously-stored flow setpoint signal f_(sp) (k), the discrete air flowsignal z(k), and a deadzone of nonlinearity.

Controller output circuit 134 receives the controller error signal e_(c)(k) from controller error circuit 132 and computes a pulse signal τ_(d)(k) to timer 136 based on a desired pulse width τ(k), a minimum pulsewidth τ_(min), a maximum pulse width τ_(max), a decay rate ζ, a systemgain g_(max) and the controller error signal e_(c) (k). The pulse widthsignal τ(k) represents the change in position for actuator 72. Timer 136receives the pulse width signal τ(k) and issues the actuator outputsignal u(t) to actuator 72 (FIG. 2). Actuator 72 receives the actuatoroutput signal u(t) from actuator output 74 via conductor 76 and adjuststhe position of damper 68 so that environment 66 is appropriatelycontrolled.

The operation of flow controller circuit 125 is discussed in more detailas follows. Sampler 130 converts the continuous time measurement signalz(t) to a discrete air flow signal z(k). Controller error circuit 132receives the discrete air flow signal z(k) and computes the controllererror signal e_(c) (k). Controller error circuit 132 includes a deadzonecircuit 138, a controller error signal circuit 142, and a summer 144.Summer 144 calculates a setpoint tracking error signal e_(sp) (k) basedon the difference between the discrete air flow signal z(k) and the flowsetpoint signal f_(sp) (k). The flow setpoint signal f_(sp) (k) isrelated to the position to which actuator 72 should have been moved (thedesired air flow rate) in the previous cycle and may be user input orcalculated by the controller algorithm or other hardware or softwarecomponents in system 10. The flow setpoint signal f_(sp) (k) iscalculated in response to temperature, air flow or other systemparameters. More specifically, the setpoint tracking error signal e_(sp)(k) is calculated by summer 144 as follows:

    e.sub.sp (k)=f.sub.sp (k)-z(k)                             (2)

Deadzone circuit 138 also receives the discrete air flow signal z(k) andcomputes the deadzone of nonlinearity.

The deadzone of nonlinearity is dependent on the amount, variance andstandard deviation of noise in the discrete air flow signal z(k). It isadaptively calculated and adaptively related to the setpoint trackingerror signal e_(sp) (k) insofar as memory 102 stores the deadzone ofnonlinearity which was calculated in the previous cycle of flowcontroller circuit 125. The deadzone of nonlinearity depends on thechosen system feedback gain g_(max) and the chosen decay rate ζ forcircuit 134.

Controller error signal circuit 142 receives the setpoint tracking errorsignal e_(sp) (k) from summer 144, the deadzone of nonlinearity fromdeadzone circuit 138, and calculates the controller error signal e_(c)(k) by applying the deadzone of nonlinearity to the setpoint trackingerror signal e_(sp) (k) to reject measurement noise. Therefore, thecontroller error signal e_(c) (k) is not necessarily the setpoint error.It is the value calculated by controller error signal circuit 142 afterthe setpoint tracking error signal e_(sp) (k) has been processed toeliminate noise. Thus, the user can adjust the performance of flowcontroller circuit 125 by selecting a parameter that affects thetradeoff between tracking capability and noise rejection.

Controller output circuit 134 receives the controller error signal e_(c)(k) from controller error signal circuit 142 and generates the new pulsewidth signal τ(k) representative of the desired air flow or desiredposition of actuator 72. Controller output circuit 134 includes adesired pulse width circuit 150 and a pulse width modulation logiccircuit 152. Pulse width circuit 150 receives the controller errorsignal e_(c) (k) and initially calculates the desired pulse width τ_(d)(k) based on the following equation: ##EQU2## wherein g_(max) representsthe maximum system gain.

The discrete-time integrator is stable only if the system feedback gainis greater than zero and less than approximately two times the inverseof the gain of flow controller circuit 125. Therefore, a preferablestability range for Equation 5 is calculated as follows: ##EQU3## whereK is the proportional gain of controller 20. In order to guarantee flowcontroller circuit 125 is stable under all operating conditions, thesystem feedback gain g_(max) used in Equation 6 is derived from theworst-case (maximum) gain of the time-varying integrator. Preferably,the following estimate of the worst-case system gain g_(max) is used inEquation 5: ##EQU4## The factor of 5 accounts for the effects of theposition of actuator 72 and the pressure ratio on the gain. The termf_(rated) is the flow rate at a nominal static pressure (e.g., one inchof water) when damper 68 is completely open. The factor of √3 accountsfor the fact that the static pressure encountered in practice may belarger than the nominal static pressure by a factor of 3. The term Tdenotes the stroke time of actuator 72. Typically, g_(max) is within arange from 5.77 to 1371 CFM/sec.

Pulse width modulation circuit 134 receives the desired pulse widthsignal τ_(d) (k) and issues the pulse signal τ(k) to timer 136 based onthe following relationship: ##EQU5## where τ_(min) is the minimum pulsewidth, τ_(max) is the maximum pulse width and ζ is the decay rate underworst case conditions.

Therefore, pulse width modulation circuit 134 provides timer 136 withthe maximum pulse width τ_(max) when the controller error signal e_(c)(k) is large, the minimum pulse width τ_(min) when the controller errorsignal e_(c) (k) is small, 0 when the controller error signal e_(c) (k)is very small and the desired pulse width τ_(d) (k) when the desiredpulse width τ_(d) (k) is greater than the minimum pulse width τ_(min)and less than or equal to the maximum pulse width τ_(max). Referring toFIG. 5 and Equation 6, the pulse width signal τ(k) drives actuator 72for the maximum amount of time when the controller error signal e_(c)(k) is very large as represented by a τ_(max) point 154 (FIG. 5). Whenthe controller error signal e_(c) (k) is small (i.e., τ_(min) <|τ_(d)(k)|≦τ_(max)), actuator 72 is driven the desired amount of time (i.e.τ(k)=τ_(d) (k)) as represented by the linear portion of the graphbetween τ_(max) point 154 and a τ_(min) point 156. Actuator 72 is drivenfor a minimum amount of time when the controller error signal e_(c) (k)is smaller as represented by τ_(min) point 156.

As previously described in conjunction with controller error circuit132, a pulse-width modulated device with high-gain feedback, such asconstant-rate actuator 72, is susceptible to measurement noise whichresults in an increase in the average duty cycle of actuator 72.Therefore, controller 20 needs some ability to reject measurement noise.

During every cycle of operation of flow controller circuit 125, thedeadzone of nonlinearity is applied to the setpoint tracking errorsignal e_(sp) (k) to reject measurement noise and results in thecontroller error signal e_(c) (k). The deadzone of nonlinearity dependson the magnitude of the measurement noise and the acceptable probabilitycontroller 20 will issue a pulse width switching signal u(t) that movesthe flow signal f(t) away from the flow setpoint signal f_(sp) (k) whenthe flow signal f(t) is exactly equal to the flow setpoint signal f_(sp)(k). This probability is represented by p. The deadzone of nonlinearityalso depends on the system feedback gain g_(max) and the decay rate ζ inEquations 5 and 8.

Referring to FIG. 6, the pulse signal τ(k) and the deadzone ofnonlinearity have a direct effect on the setpoint tracking error signale_(sp) (k). The minimum setpoint tracking error signal e_(sp) (k) causesa pulse to be issued by controller output circuit 134 and is dependenton the deadzone of nonlinearity, the system gain g_(max), and the decayrate ζ. Assuming the measurement noise is normally distributed and thereis an acceptable value of p, deadzone circuit 138 preferably calculatesthe deadzone of nonlinearity as follows: ##EQU6## wherein: ##EQU7##where Z_(p/2) is the upper p/2 percentage point of the standard normaldistribution, R(k) is the variance of the measurement noise, and e_(t)is the minimum magnitude of the controller error such that a pulse isissued. The parameter p is preferably any number between 0 and 1 and canbe specified by the user to achieve a tradeoff between setpoint trackingand duty cycle. For most applications involving cascaded flow and zonetemperature control, p is small (for example, preferably 0.01). However,there are some applications, such as zone balancing, in which the usermay make p large (e.g., 0.2-0.3) so that a rapid response with a minimalsteady-state error is achieved.

Generally, the variance of the measurement noise changes with time so itis estimated as controller 20 operates. The following equation estimatesthe variance of the measurement noise: ##EQU8## wherein w represents thefilter factor which is calculated as follows: ##EQU9## where T is thestroke time of actuator 72 and t_(s) is the sampling interval. Timer 136receives the pulse signal τ(k) from pulse width modulation logic circuit152 and issues the actuator output signal u(t) to actuator 72 fromactuator output 74 via conductor 76 which adjusts the position of damper68 so that environment 66 is appropriately controlled. A pulse widthswitching signal of 1, 0 or -1 represents positive movement, no movementor negative movement, respectively, of actuator 72, and is issued bytimer 136 during each cycle of operation of flow controller circuit 125.As illustrated in FIG. 4, this cyclical operation of the software-basedcontrol algorithm used in flow controller circuit 125 then begins againby air flow sensor 52 generating the continuous time measurement signalz(t) based on the flow signal f(t) and the measurement noise signaln(t).

Preferably, controller 20 is configured by controller executed software.Exemplary controller executed software is provided in FIGS. 7A-B andconfigures controller 20 for the operations discussed with reference toFIGS. 4-7. The software shows basic data collection operations andsignal calculations for controller 20. Alternatively, a hardware controlcircuit, or other software may be utilized to calculate the deadzone ofnonlinearity, the flow setpoint signal f_(sp) (k) and the actuatoroutput signal u(t) for actuator 72 and controller 20.

In an alternative preferred embodiment, the algorithm executed by thecontroller 20 has been improved to enhance the environment controlsystem 10. These improvements are represented in FIGS. 8-10, whichdisclose the components of flow controller circuit 125'. Theimprovements to the algorithm include reducing the number of variableswhich must be manually set, and replacing these manually set variableswith a series of functions which are cyclically performed by thealgorithm for automatically selecting and updating these variables. Thisimprovement allows the algorithm to switch the controller 20 back andforth between one mode which adjusts the flow control very quickly inresponse to set point changes, and a second mode in which the flowcontrol is adjusted more slowly. The improved algorithm also provides aflow control system with more robust noise rejection capabilities whichfurther enhances the control and operation of the flow controller 20.Finally, the algorithm has been redesigned to provide greater and moreaccurate setpoint tracking while reducing the duty cycle or load placedupon the actuator 72. The duty cycle refers to the motion required bythe actuator, which could include stepper motors, synchronous motors, orsolenoids, for moving a damper. This improvement serves to increase thelifespan of the actuator 72 by reducing the amount of unwanted movementby the actuator in responding to changes caused by noise, as opposed tonecessary movement by the actuator for adjusting the flow control.Accordingly, one skilled in the art will appreciate the benefitsprovided by the improvements to the flow control algorithm of thealternative preferred embodiment of the present invention.

As discussed above, the previous algorithm implemented a time-varyingdeadzone of nonlinearity that is a function of the variance of themeasurement noise. This previous algorithm provides excellent set-pointtracking and disturbance rejection for situations where a high actuatorduty-cycle is acceptable by choosing higher values for p (p=0.1-0.5).Further, an acceptable setpoint tracking performance and disturbancerejection can be achieved with an extremely low actuator duty-cycle bychoosing significantly lower values for p (p=0.01). The previousalgorithm also relies upon manually setting a proportionality constantthat does not change with time, or change in response to switchingbetween various operating modes. Thus, the previous algorithm provided atrade-off between set-point tracking and actual duty-cycle.

However, situations exist where significantly higher set-point trackingperformance and disturbance rejection performance is desirable alongwith a low actuator duty-cycle. It is also desirable to provide anenvironment control system 10 which is capable of switching betweenvarious operating modes for adjusting the setpoint tracking performance.Accordingly, the goal of the alternative embodiment of the presentinvention is to optimize the set-point tracking and disturbancerejection performance along with the actuator duty-cycle performance,rather than providing a trade off between the two. This is achieved byautomatically changing and adjusting the proportionality constant withina predetermined range of values. Such an optimized algorithm providesfor a significantly more efficient control system while also reducingthe operational requirements placed upon the flow control actuator 72.

The previously preferred embodiment requires that the proportionalityconstant be set manually as a function of the probability p thatcontroller 20 will issue a pulse width switching signal u(t) that movesthe flow signal f(t) away from the flow setpoint signal f_(sp) (k) whenthe flow signal f(t) is exactly equal to the flow setpoint signal f_(sp)(k). As set forth above, the proportionality constant Z_(p/2) is the p/2percentage point of the standard normal distribution. As discussed, thepreferred fixed value for Z_(p/2) is 2.58.

In the alternative preferred embodiment, a method for automaticallycalculating and changing the proportionality constant has beendeveloped. In this embodiment, the proportionality constant isrepresented by C(k). This method involves setting the proportionalityconstant C(k) equal to zero after a substantial change in the flowsetpoint signal f_(sp) (k), then returning the proportionality constantC(k) to a conservative setting using an exponential function after theflow rate signal f(t) has overtaken the flow setpoint signal f_(sp) (k).

The result of this method is that the controller 20 can be switched backand forth between a first operating mode and a second operating mode.Preferably, the first and second operating modes are defined by aconservative mode and an aggressive mode, respectively. Morespecifically, the algorithm provides a function which can instantlyswitch from the first mode to the second mode for aggressively and moreaccurately controlling the set-point tracking. When logic within thealgorithm detects a substantial change in the flow setpoint signalf_(sp) (k), the proportionality constant C(k) is set to zero, whichinstantly switches from the first mode, or default mode, into the secondmode. As the algorithm logic detects that the flow rate signal f(t) hasovertaken the flow set-point signal f_(sp) (k), the proportionalityconstant C(k) is increased exponentially from zero to a maximum value,preferably 2.58 if p=0.01, which gradually, albeit exponentially overtime, changes the controller 20 from the second (aggressive) operatingmode back into the first (conservative) operating mode. The algorithmwill then remain in the first (conservative) operating mode until asubstantial change in the flow setpoint signal f_(sp) (k) is detected.This exponential change of the proportionality constant C(k) is shown inFIG. 10 where the axis 220 represents the proportionality constantrange, and the axis 222 represents discrete time. FIG. 10 furtherillustrates exemplary areas on the graph which represent the firstoperating mode 224 and the second operating mode 226. The algorithm andfunctions associated with adjusting the proportionality constant C(k)for implementing automatic mode switching are discussed in more detailbelow. The benefits provided by this improvement to the algorithm are afaster controller response time, less actuator motion, fewer actuatorstart-stops, and a simplification to the user interface. Thissimplification is achieved because the proportionality constant C(k)does not have to be manually set within the algorithm.

The design of a control algorithm should take into account the behaviorof the system and the desired performance objectives. Under normaloperation, the most important control performance metrics are gooddisturbance rejection and high reliability. However, duringcommissioning and manual troubleshooting, a fast response to setpointchanges is the most important control performance metric. It has alreadybeen shown that the flow system may be modeled as a purely integratingsystem. As such, a proportional-only controller is recommended forpurely integrating systems. The control algorithm described below andassociated with the alternative preferred embodiment is aproportional-only controller that is tuned to provide deadbeat controlwhen the system gain is largest.

Referring now to FIG. 8, a modified block diagram is shown whichillustrates the controller circuit 125' for implementing thisalternative preferred embodiment of the present invention. In thisalternate embodiment, controller circuit 125' has been modified toinclude an additional function represented by the proportionalityconstant circuit 200, which is part of modified controller error circuit132', and is responsible for cyclically computing the proportionalityconstant C(k). However, it should be understood that whileproportionality constant circuit 200 provides additional functionalityto controller circuit 125', the deadzone circuit 138 and the controllererror signal circuit 142 of controller circuit 125' operate insubstantially the same manner as described above. Thus, in thisalternative embodiment, controller 20 is programmed to operate as a flowcontroller circuit 125' which generates an actuator output signal u(t)to position damper 68 (FIG. 2). Accordingly, it should be understoodthat controller circuit 125' also includes an anti-aliasing filter 128,a sampler 130, a controller output circuit 134, and a timer 136 whichoperate in substantially the same manner as with the components ofcontroller circuit 125 described above (with respect to FIG. 4).

With continued reference to FIG. 8, the continuous-time measurementsignal, z(t), is first filtered with an analog low-pass filter 128 sothat noise at frequencies higher than the Nyquist frequency of thesampler is rejected. Sampler 130 receives the filtered continuous timemeasurement signal z(t) and provides the filtered signal z(t) tocontroller error circuit 132' as a discrete time air flow signal z(k)which represents the measured airflow signal from flow sensor 52 at thekth instant in time. Controller error circuit 132' receives the discreteairflow signal z(k) from sampler 130, and computes a controller errorsignal e_(c) (k) based on a previously stored flow setpoint signalf_(sp) (k), the discrete airflow signal z(k) and a deadzone ofnonlinearity.

As the output of sampler 130, the discrete time air flow signal z(k) iscompared to the flow setpoint signal f_(sp) (k) by summer 144 togenerate the setpoint error e_(sp) (k). The proportionality constantC(k), which controls the operating mode of controller 20, is computedduring each cycle as a function of the flow setpoint signal f_(sp) (k)and the discrete time air flow signal z(k) by proportionality constantcircuit 200. The proportionality constant C(k) produced byproportionality constant circuit 200 is then used by deadzone circuit138 for computing the deadzone of nonlinearity as previously disclosed.Accordingly, the proportionality constant circuit 200 is primarilyresponsible for implementing the mode switching logic associated withthe alternative embodiment of the present invention. The logic andfunctions executed by proportionality constant circuit 200 are describedin more detail below.

The controller error e_(c) (k) is computed from the setpoint errore_(sp) (k) by passing the setpoint error e_(sp) (k) through the deadzoneof nonlinearity produced by block 138. As disclosed above, thiscomputation is performed by the controller error signal circuit 142. Inthis alternative embodiment, the magnitude of the deadzone is determinedfrom an estimate of the absolute value of the noise, and logic withinthe algorithm to detect a large setpoint change. The desired pulse widthτ_(d) (k) is computed based on the controller error by pulse widthcircuit 150. The actual pulse width τ(k) is computed by passing thedesired pulse width τ_(d) (k) through the pulse-width modulation logiccircuit 152. Finally, the actuator 72 is rotated by sending the pulsewidth command τ(k) to a timer 136 that operates the actuator 72 (FIG.2).

Prior to executing the mode switching logic and computing theproportionality constant C(k), the standard deviation σ(k) of the noisemust be calculated. This function is also preferably performed byproportionality constant circuit 200. Also as set forth above, in thepreviously preferred embodiment, a heuristic method for estimating thevariance of the measurement noise was utilized (equation 9). As can beseen form a brief review of equation 9, forming part of the previousalgorithm, the standard deviation was determined from the square root ofan exponentially weighted average of the square of a noise variable.However, as an enhancement to the design of the algorithm associatedwith the alternative preferred embodiment, the standard deviation may beestimated directly from an exponentially weighted average of theabsolute value of the same noise variable. The advantage to thisimprovement is a lower computational effort, and this method providesrobustness to outliers which may be present in the noise signal. Theabsolute value of the noise is computed by passing the flow signal f(t)first through a high-pass filter, then through a magnitude nonlinearity,and finally through a low-pass filter. The highpass filter is chosen asfollows: ##EQU10##

This filter is used because the flow rate will ramp nearly linearlyafter a large setpoint change whenever t_(s) <<T, and this filtercancels such a ramp. The square root of six makes the standard deviationof e_(n) equal the standard deviation of the noise when the noise isuncorrelated. The standard deviation of the noise is then estimated asfollows:

    σ(k)=(1-w)σ(k-1)+1.25w|e.sub.n (k)|(12)

The factor of 1.25 makes the expected value of σ equal the standarddeviation of e_(n) when e_(n) is normally distributed. The parameter wis a filter weight which is specific to the performance of theindividual system. The following choice will make the noise estimatorfaster when the actuator is faster: ##EQU11## where t_(s) is the sampleperiod and T is the stroke time of the actuator. Accordingly, this valueof σ(k) which estimates the noise within the measured flow signal f(t)is used to compute the magnitude of the deadzone of nonlinearity, and isdiscussed in more detail below.

Flow measurements, especially air flow measurements, are prone to highlevels of noise because of turbulence. Therefore, the controller 20should have some ability to reject this noise. A preferred method forrejecting noise is to use a deadzone of nonlinearity in the controlalgorithm. The logic for the deadzone nonlinearity is as follows:##EQU12## where Δ is the magnitude of the deadzone of nonlinearity. Thechoice of the deadzone magnitude should depend on the absolute value ofthe measurement noise (computed above), and on the acceptableprobability p that the controller 20 will issue a pulse u(t) that movesthe flow rate signal f(t) away from the flow setpoint signal f_(sp) (k)when the flow rate f(t) is exactly equal to the flow setpoint f_(sp)(k).

The magnitude of the deadzone Δshould also be modulated after a largesetpoint change so that it will not impede the response when thecontroller is being operated manually. This is accomplished by switchingbetween two control modes; preferably a conservative mode and anaggressive mode. The mode switching logic decides that if there is alarge flow setpoint change f_(sp) (k), and if this change results in alarge error, then the magnitude of the deadzone is zero. This condition(Δ=0) defines the switch from the conservative mode to the aggressivemode. This condition persists until the flow rate f(t) overtakes theflow setpoint f_(sp) (k). After the flow rate f(t) overtakes the flowsetpoint f_(sp) (k), the deadzone gradually, albeit exponentially overtime, recovers from zero to its conservative steady-state value. Thiscondition defines the automatic switch from the aggressive mode to theconservative mode. As previously discussed, the automatic switch fromthe aggressive mode to the conservative mode occurs exponentially over aperiod of time, preferably 15 seconds. In the conservative mode, themagnitude of the deadzone is calculated as follows:

    C(k)=(1-w)C(k-1)+wZ.sub.p/2                                (15)

    Δ(k)=max C(k)σ(k)-e.sub.t, 0!                  (16)

where ##EQU13## is the p/2 percentage point of the standard normaldeviate, and e_(t) is the smallest value of the controller error thatwill produce a pulse. As disclosed above, C(k) is the proportionalityconstant. In the pseudo code shown in FIG. 9A and 9B, theproportionality constant C(k) is represented by Z.

In the aggressive mode, C(k)=0 and Δ(k)=0. The event that triggers achange in the control algorithm from the first (conservative) operatingmode to the second (aggressive) operating mode is as follows: ##EQU14##This change is preferably instantaneous or nearly instantaneous. Theevent that triggers a change in the control algorithm from the second(aggressive) mode to the first (conservative mode) is as follows:

    sign e.sub.sp (k)!≠sign e.sub.sp (k-1)! and |f(k)-f(k-1)|>|f.sub.sp (k)-f.sub.sp (k-1)|                                           (18)

Preferably, this change occurs exponentially over time.

Finally, as set forth above, the algorithm associated with thepreviously preferred embodiment utilized a worse-case stability marginthat varies with the control error. This previously preferred design isbeneficial when the controller implemented thereby is used with asynchronous electric motor activated with triacs. In the algorithmassociated with the alternative preferred embodiment, this stabilitymargin has been made a constant for all controller errors because theimproved algorithm is preferably used in conjunction with a steppermotor. The implementation of this uniform stability margin is shown asbracketed element 210 in the pseudo code shown in FIG. 9B. The mostsignificant benefit of this enhancement to the algorithm associated withthis alternative preferred embodiment is a simplification of the controllogic.

It is understood, that while the detailed drawings and specific examplesgiven describe a preferred exemplary embodiment of the presentinvention, they are for the purpose of illustration only. The inventionis not limited to the precise details and conditions disclosed. Forexample, although a particular application is discussed, otherapplications may utilize the flow controller of the present invention.Also, although particular facility management systems and components aresuggested, the system may be configured for various other HVAC systems.The system may easily be configured to utilize metric units. Also,single lines in the various Figures may represent multiple conductors.Various changes may be made to the details disclosed without departingfrom the spirit of the invention which is defined by the followingclaims.

What is claimed is:
 1. An environment control system including an airunit for providing air flow to an environment, the air unit beingoperatively associated with a controller and controlling an amount ofthe air flow in accordance with a flow set-point signal from thecontroller, the controller comprising:a flow sensor exposed to the airflow provided by the unit, the flow sensor generating a flow signalrepresentative of an amount of the air flow provided to the environment;a processor connected to the flow sensor, the processor configured tocyclically receive the flow signal and generate a controller outputsignal in response to the flow signal and the flow setpoint signal, thecontroller output signal being provided to the air unit to cause the airunit to provide the amount of the air flow represented by the flowsetpoint signal, the processor calculating the controller output signalin accordance with a setpoint error signal, a proportionality constant,and a deadzone of nonlinearity, whereby the processor calculates thedeadzone of nonlinearity in accordance with a variance of the flowsignal; the processor switching the controller between a first operatingmode and a second operating mode in response to a set of conditionsassociated with the flow setpoint signal, said first operating modebeing a default mode; wherein the processor changes the proportionalityconstant stepwise from a first predetermined constant to a secondpredetermined constant thereby instantaneously switching the environmentcontrol system from the first operating mode to the second operatingmode in response to a predetermined change in the setpoint signal forclosely tracking changes in the setpoint error signal; and wherein theprocessor exponentially changes the proportionality constant from thesecond predetermined constant to the first predetermined constantthereby gradually switching the environment control system from thesecond operating mode to the first operating mode in response to apredetermined change in the flow signal for normally tracking changes inthe setpoint error signal.
 2. The controller of claim 1 wherein thefirst operating mode is a conservative operating mode and the secondmode is an aggressive operating mode.
 3. The controller of claim 1wherein the setpoint error signal is related to the difference between aprevious flow setpoint signal and the flow signal.
 4. The controller ofclaim 1 including a memory for storing a software-based controlalgorithm executed by the processor for generating the flow setpointsignal in accordance with the software-based control algorithm.
 5. Thecontroller of claim 3 including a memory for storing a software-basedcontrol algorithm and the processor cyclically generates the controlleroutput signal in accordance with cyclical operation of thesoftware-based control algorithm, and wherein the previous flow setpointsignal is from a most recent previous cycle of operation of the controlalgorithm.
 6. The controller of claim 4 wherein the deadzone ofnonlinearity is stored in the memory and recalculated each cycle ofoperation of the control algorithm.
 7. The controller of claim 6 whereinthe deadzone of nonlinearity is adaptively adjusted by the standarddeviation of a noise signal associated with the flow signal.
 8. Thecontroller of claim 6 wherein the deadzone of nonlinearity is adaptivelyadjusted by the standard deviation of the absolute value of a noisesignal associated with the flow signal.
 9. A controller for use in anenvironment control system including an air duct including a damperoperatively associated with an actuator, the actuator positioning thedamper so that the damper provides a rate of air flow to an environmentin response to an actuator control signal, the actuator beingoperatively coupled to the controller, the controller comprising:sensormeans for generating an actual flow signal representative of the rate ofthe air flow provided across the damper; and processor means connectedthe sensor means for cyclically receiving the actual flow signal fromthe sensor means, and for cyclically generating the actuator controlsignal in response to the actual flow signal, wherein the actuatorcontrol signal is related to a desired rate for the rate of the air flowprovided across the damper, the processor means calculating the actuatorcontrol signal in accordance with a setpoint error signal and a deadzoneof nonlinearity, wherein the deadzone of nonlinearity is calculated inaccordance with an estimate of the standard deviation of a noise signalassociated with the actual flow signal; the processor means switchingthe controller between a first operating mode and a second operatingmode in response to a set of conditions associated with the flowsetpoint signal; wherein the processor means changes the proportionalityconstant stepwise from a first predetermined constant to a secondpredetermined constant thereby instantaneously switching the controllerfrom the first operating mode to the second operating mode in responseto a predetermined change in the setpoint signal for closely trackingchanges in the setpoint error signal; and wherein the processor meansexponentially changes the proportionality constant from the secondpredetermined constant to the first predetermined constant therebygradually switching the controller from the second operating mode to thefirst operating mode in response to a predetermined change in the flowsignal for normally tracking changes in the setpoint error signal. 10.The controller of claim 1 wherein the first operating mode is aconservative operating mode and the second operating mode is anaggressive operating mode.
 11. The controller of claim 9 wherein thesetpoint error signal is related to a difference between a flow setpointsignal generated in a previous cycle of operation of the processingmeans and the actual flow signal received in a current cycle ofoperation of the processing means.
 12. The controller of claim 9including memory means for storing a software-based control algorithmand wherein the processor means generates the actuator output signal inaccordance with the software-based control algorithm.
 13. The controllerof claim 10 including memory means for storing a software-based controlalgorithm and the processor means cyclically generates the flow setpointsignal in accordance with cyclical operation of the software-basedcontrol algorithm, and wherein the previous cycle is from a most recentprevious cycle of operation of the control algorithm.
 14. The controllerof claim 9 including memory means for storing a software-based controlalgorithm and the processor means cyclically generates the flow setpointsignal in accordance with cyclical operation of the software-basedcontrol algorithm, and wherein the deadzone of nonlinearity is stored inthe memory means and recalculated each cycle of operation of the controlalgorithm.
 15. The controller of claim 13 wherein the deadzone ofnonlinearity is related to a previous deadzone of nonlinearitycalculated in a previous cycle.
 16. The controller of claim 14 whereinthe deadzone of nonlinearity is adaptively related to the variance. 17.In a control system including a unit for providing a flow of a fluid, acontroller for providing a controller output signal, and a flow sensorfor providing an actual flow signal, the unit being operativelyassociated with a controller and controlling an amount of the flow inaccordance with a controller output signal from the controller, the flowsensor being exposed to the flow provided by the unit, the flow sensorgenerating the actual flow signal representative of the amount of flowprovided, a method of controlling the amount of the flow provided by theunit comprising steps of:receiving the actual flow signal from the flowsensor; determining a setpoint error signal based on a flow setpointsignal and the actual flow signal; calculating a proportionalityconstant for switching the control system between a first operating modeand a second operating mode in response to a set of conditionsassociated with the flow setpoint signal; calculating a deadzone ofnonlinearity in accordance with a variance of the flow signal due tonoise, and in accordance with the proportionality constant; applying thedeadzone of nonlinearity to the setpoint error signal to develop thecontroller output signal; and providing the controller output signal tothe unit.
 18. The method of claim 17 wherein the first operating mode isa conservative operating mode and the second operating mode is anaggressive operating mode.
 19. The method of claim 17 wherein thecontroller changes the proportionality constant stepwise from a firstpredetermined constant to a second predetermined constant therebyinstantaneously switching the control system from the first operatingmode to the second operating mode in response to a predetermined changein the setpoint signal for closely tracking changes in the setpointerror signal.
 20. The method of claim 17 wherein the controllerexponentially changes the proportionality constant from a secondpredetermined constant to a first predetermined constant therebygradually switching the control system from the second operating mode tothe first operating mode in response to a predetermined change in theflow signal for normally tracking changes in the setpoint error signal.21. The method of claim 17 wherein the step of calculating the deadzoneof nonlinearity includes calculating the standard deviation of theabsolute value of a noise signal associated with the flow signal. 22.The method of claim 17 including the step of high pass filtering theflow signal for rejecting ramping attributes associated with the actualflow signal.
 23. The method of claim 17 wherein the controller includesa memory and a processor, the memory including a software-based controlalgorithm and the processor generating the actuator output signal inaccordance with the software-based control algorithm.
 24. The method ofclaim 17 wherein the deadzone of nonlinearity is adaptively calculated,whereby the deadzone of nonlinearity is related to previous values ofthe deadzone of nonlinearity.